1. Field of the Invention
The present invention relates to a noise suppressor for removing noise from an audio signal.
2. Description of the Related Art
Fixed and mobile telephone sets are often used for input of speech. Frequently the input includes noise, such as noise at a traffic intersection or in an office, that makes the speech difficult to understand and may cause automatic voice recognition facilities to operate incorrectly. The input signal must accordingly be processed to remove the noise. Various methods have been proposed.
One of these is the SPAC method proposed by Takasugi et al. in “Jikosokankansu wo riyo shita onsei shori hoshiki (SPAC) no kino to kihon tokusei” (Processing of SPAC (Speech Processing system by use of AutoCorrelation function) and fundamental characteristics), IECE of Japan, J62-A, No. 3, pp. 175-182, March 1979. The autocorrelation function ψ of a periodic wave has the same frequency components as the original signal and its periodicity is easy to detect. The amplitude components of the autocorrelation function ψ of random noise, however, are concentrated around the origin. The SPAC method uses these differing autocorrelation properties by taking the waveform of a short-term autocorrelation function of the speech signal and splicing it to reproduce the speech signal. This reduces the noise level and improves the signal-to-noise ratio. When applied to a quantized signal, the SPAC method greatly reduces the noise level during pauses, making for much more pleasant listening.
The SPAC method, however, requires extensive computation to derive the autocorrelation function. Another problem is that the autocorrelation process squares the amplitudes of the frequency components, thereby distorting the reproduced speech signal. The distortion can be reduced by an equalization process that decomposes the input signal into several frequency bands and divides the signal in each frequency band by its mean square root, but this is also computationally expensive, and some distortion still remains.
Another known noise reduction method is to store the spectrum of noise averaged over intervals in which speech is absent, and subtract this noise spectrum from the spectrum of the speech signal in intervals in which speech is present, as described by Boll in “Suppression of acoustic noise in speech using spectral subtraction”, IEEE Trans. ASSP-27, No. 2, pp. 113-120, 1979. This method, however, rests on the assumption that the ambient noise maintains a steady state. Spectral subtraction is effective in removing regularly occurring noise and small noise components, but it fails in an environment in which the noise level is high and the noise is irregular.
Another known method of reducing noise is to compare signals picked up by two microphones, one of which receives the intended speech signal and ambient noise while the other receives only the ambient noise, but besides requiring an extra microphone, this method requires extensive processing and is impractical in devices that do not provide a suitable location for mounting the second microphone.
There is a need for a single-microphone noise suppression method that does not require extensive computation or other processing.